Justin Gottschlich

Founder, CEO & Chief Scientist @ Merly Inc.

Adjunct Lecturer @ Stanford University

Steering Committee Chair, ACM SIGPLAN Machine Programming Symposium (MAPS)

Ex-Principal AI Scientist & Director/Founder of Machine Programming Research (Intel Labs)

Highlights

My machine programming company's website: http://merly.ai

My Machine Programming & Technology YouTube Channel (subscribe & stay updated)

Keynote at LADSIOS (co-located with VLDB '21): "Machine Programming and the Future of Software Development"

New demo of one of our production quality MP systems: AutoPerf

Our team, joint w/ MIT & Microsoft, won two awards at SIGMOD '21!

Keynote @ MIT's DSAIL 2021 virtual retreat: "A Glimpse Into Machine Programming @ Intel Labs"

Invited talk @ UWisc's 2020 MLOS Seminar Series: "Machine Programming: Challenges and Opportunities" (video)

Keynote @ Penn's PRECISE 2019 Industry Day: "Machine Programming: The Future of Autonomy"

Our research has been highlighted by venues like Wall Street Journal, DeepLearning.ai, Communications of the ACM, New York Times, SDTimes, Economic Times, Venturebeat, and Wharton, and many others.

Recent Committees

NeurIPS '22, ICLR'22, PLDI'22, CGO'21, NeurIPS'21, AIDB'21, PACT'21, FSE'21, OOPSLA'21, MAPS'21 (SC chair), ICML'21, USENIX ATC'21, ICLR'21, MLSys'21, NeurIPS'20, MAPL'20 (SC chair), JPDC'20, aiDM '20, TheWebConf'20, MLSys'20, PACT'19 (SRC), SysML'19, MAPL'18 (general chair)

Contact: justin.gottschlich@merly.ai

Brief Biographical Sketch

In December 2021, I founded Merly, Inc., a Silicon Valley start-up aiming at disrupting software development. I am currently Merly's Chief Executive Officer (CEO) and Chief Scientist. Merly aims to (i) improve the rate at which we develop software while concurrently (ii) improving its quality. We achieve this by employing a variety of automation techniques -- otherwise known as machine programming -- such as deep neural networks and formal methods. Learn more here (https://merly.ai)!

Previously, I founded and led the Machine Programming Research group at Intel Labs. Machine programming (MP) is a new field of research that uses automation to improve the rate at which we develop software (e.g., the time it takes a developer to write, maintain, and test code) and improve its associated quality characteristics (e.g., performance, correctness, security, maintainability, etc.). We generally consider MP as a fusion of machine learning and formal methods, which rely heavily on programming languages and systems. We provide a brief overview of MP in our “Three Pillars of Machine Programming” vision paper (see Armando Solar-Lezama's website for a deeper dive).

In academia, I am a lecturer at Stanford University, where I teach the "Introduction to Machine Programming" graduate computer science course.

I have ~40 peer reviewed papers, ~70 issued patents, and ~130 patents pending. I've been lucky enough to have been invited to give talks at places like Berkeley, BMW, DARPA, IBM Research, MIT, Penn, Stanford, UCLA, University of Washington, VMWare, and Wharton, amongst others. I've had the tremendous honor to give keynote addresses at places like VLDB (LADSIOS), University of Pennsylvania, the US Department of Energy, and MIT. My team's research has been highlighted by venues like The Wall Street Journal, DeepLearning.ai, Communications of the ACM, MIT Technology Review, The New York Times, and many others.

My (extremely dated) CV is here. Google scholar.

Recent Activity

Launched Merly.ai

Keynote address at LADSIOS (co-located with VLDB '21): "Machine Programming and the Future of Software Development"

[Milestone] 50th patent issued: "Methods and apparatus to detect side-channel attacks"

Our team, Machine Programming Research (MPR), won two awards at SIGMOD '21!

Former Students

MS advisor (University of Pennsylvania): Brad MacDonald -> Tesla

MS co-advisor (University of Pennsylvania): Celine Lee -> Intel Labs, then PhD student @ Cornell

PhD committee member (Lehigh University): PanteA Zardoshti -> Microsoft Research

PhD committee member (University of Washington): Maaz Ahmad -> Adobe Research

MS advisor (University of Pennsylvania): Akhilesh Gupta -> Apple

MS advisor (University of Pennsylvania): Sam Weintraub -> Outrider

PhD committee member (UT-San Antonio): Mohammad Mejbah ul Alam -> Intel Labs, Google

PhD committee member (Lehigh University): Wenjia Ruan -> Qualcomm

PhD co-advisor (Brown University): Irina Calciu -> VMWare Research